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Prasad Calyam (PI) 1,2,3 , Paul Schopis (Co- PI) 2,3 , Arunprasath Selvadhurai ( Software Developer) 1,3 Ohio Supercomputer Center 1 , OARnet 2 , The Ohio State University 3 , Point-of-contact: pcalyam@ osc.edu July 2012. Project Overview
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Prasad Calyam (PI)1,2,3, Paul Schopis (Co-PI) 2,3, ArunprasathSelvadhurai (Software Developer)1,3Ohio Supercomputer Center1, OARnet2, The Ohio State University3, Point-of-contact: pcalyam@osc.eduJuly 2012 • Project Overview • Goal: Instrumentation and Measurement capabilities for GENI experimenters and operations • Outcomes: • Software to perform centralized and distributed measurement orchestration and provisioning of measurements • Centralized orchestration for continuous monitoring, persistent measurements storage and processed network measurement feeds • Distributed orchestration for on-demand (real-time) measurements without need for persistent measurements storage • Measurement Service that enables users to utilize OnTimeMeasure software in GENI experiments • Registers users, slices, maintains meta-data, and allows user control of measurement service functions • Researcher Web-portal – http://ontime.oar.netfor interactive user control of measurement service • Command-line tools for measurement service control automation OnTimeMeasure Architecture OnTimeMeasure Capabilities for GENI Experimenters • What OnTimeMeasure can provide Experimenters • Data Aggregation • Your distributed data sources can be controlled and accessed (start/stop/query) in a centralized manner via web-portal or command line • Data Visualization • Measurement data graphs, dashboards • Data Analysis • Time Series with Anomalies/Time Series with Forecasts/others • Ability to use analysis of the measurements to reconfigure the measurement specifications without human intervention • Data Archive • Slice owners can access and download data and metadata • Integration with other GENI projects to extend OnTimeMeasure functionality for Experimenters: • OnTimeMeasure-ProtoGENI, OnTimeMeasure-PlanetLab - I&M service for GENI aggregate users • OnTimeMeasure-Gush - I&M service control through Experimenter workflow tool • OnTimeMeasure*-INSTOOLS** - Both active* and passive** measurements in experiment slice • OnTimeMeasure-CRON - I&M service for 10Gbps network path experiments • OnTimeMeasure-DOR – I&M Data Archive service GENI Experiment Information needed for OnTimeMeasure Integration • Control Actors • Project members or your research application that would access the data or share the data with other actors • Data Sources • Data generation tools deployed in slice nodes; the tool would communicate with other nodes to perform active measurements or inherently collects passive measurements in on-going and on-demand manners • Data Structures/Data Types • Measurement data would be stored in a data base with proper data structure and data types • Control Actions • Control start and stop of the data generation tool, control how to retrieve and utilize the data e.g., dashboard, plot, time series file with anomaly annotation NOTE: To integrate new measurement metrics of Experiments in OnTimeMeasure, we need information about your Control Actors, Data Sources, Data Structures/Data Types, and Control Actions New!OnTimeMeasure Capabilities Tutorial for Experimenters See - http://groups.geni.net/geni/wiki/OnTimeMeasureTutorial • GENI Experiment Case Studies • Case Study I: “Resource allocation in virtual desktop clouds” led by The Ohio State University • Path-based measurements of network health such as delay, available bandwidth, loss • Host-based measurements from VMware tools such as CPU, memory, number of VM connections • Case Study II: “Emulating cloud dynamics for performance sensitive applications” led by Purdue University • Path-based measurements of network health such as delay • Host-based measurements from tshark such as packet sizes for HTTP sessions • The tutorial provides step-by-step instructions for GENI experimenters to learn about the main instrumentation and measurement capabilities of OnTimeMeasure that can be used in an integrated manner with Flack/ProtoGENI, INSTOOLS, Gush, OMNI and PlanetLab *NSF Award Number CNS-0940805: This material is based upon work supported by the National Science Foundation under Grant No. CNS-0940805. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of BBN Technologies, Corp., the GENI Project Office, or the National Science Foundation.
